Remove line numbers, cleanup

Author: xl0

README.md

@@ -16,12 +16,6 @@
 - [TinyGrad](https://github.com/tinygrad/tinygrad): 🫀 [Lovely
   Grad](https://github.com/xl0/lovely-grad)
 
-##### Proompting
-
-- Log prompts with 💌 [Lovely
-  Prompts](https://github.com/xl0/lovely-prompts)
-- Better LangChain: 😎 [Proompter](https://github.com/xl0/proompter)
-
 ##### Community
 
 - [Discord](https://discord.gg/qBaqauUWXP)

index_files/figure-commonmark/cell-17-output-1.svg

@@ -3,7 +3,7 @@
 # %% auto 0
 __all__ = ['Lo', 'lo']
 
-# %% ../nbs/10_lo.ipynb 4
+# %% ../nbs/10_lo.ipynb
 from typing import Any, Union, Optional as O
 from matplotlib import pyplot as plt, axes, figure
 
@@ -18,7 +18,7 @@
 from .repr_rgb import RGBProxy
 from .repr_chans import ChanProxy
 
-# %% ../nbs/10_lo.ipynb 5
+# %% ../nbs/10_lo.ipynb
 class Lo():
     """Lo and behold! What a lovely `numpy.ndarray`!"""
     def __init__(   self,
@@ -74,7 +74,7 @@ def plt(self):
     def __call__(self, depth=1):
         return Lo(self.x, depth=depth, color=self.color)
 
-# %% ../nbs/10_lo.ipynb 6
+# %% ../nbs/10_lo.ipynb
 def lo(x: Union[np.ndarray, np.generic],    # Your data
         plain   :bool   =False, # Show as plain text - values only
         verbose :bool   =None,  # Verbose - show values too

index_files/figure-commonmark/cell-18-output-1.svg

@@ -3,7 +3,7 @@
 # %% auto 0
 __all__ = ['chans']
 
-# %% ../nbs/05_repr_chans.ipynb 3
+# %% ../nbs/05_repr_chans.ipynb
 from typing import Any, Optional as O
 
 import numpy as np
@@ -15,7 +15,7 @@
 from .utils.config import config, get_config
 from .utils.utils import cached_property
 
-# %% ../nbs/05_repr_chans.ipynb 4
+# %% ../nbs/05_repr_chans.ipynb
 def fig_chans(  x           :np.ndarray,      # Input array
                 cmap        :str="twilight",  # Use matplotlib colormap by this name
                 cm_below    :str="blue",
@@ -50,7 +50,7 @@ def fig_chans(  x           :np.ndarray,      # Input array
     return fig_rgb(inf_cmap(x), cl=True, gutter_px=gutter_px, frame_px=frame_px, scale=scale, view_width=view_width, ax=ax)
 
 
-# %% ../nbs/05_repr_chans.ipynb 5
+# %% ../nbs/05_repr_chans.ipynb
 class ChanProxy():
     def __init__(self, x: np.ndarray):
         self.x = x
@@ -96,7 +96,7 @@ def _repr_png_(self):
             metadata={"Software": "Matplotlib, https://matplotlib.org/"})
 
 
-# %% ../nbs/05_repr_chans.ipynb 6
+# %% ../nbs/05_repr_chans.ipynb
 def chans(  x           :np.ndarray,      # Input array
             cmap        :str="twilight",  # Use matplotlib colormap by this name
             cm_below    :str="blue",

index_files/figure-commonmark/cell-19-output-1.svg

@@ -3,7 +3,7 @@
 # %% auto 0
 __all__ = ['plot']
 
-# %% ../nbs/02_repr_plt.ipynb 3
+# %% ../nbs/02_repr_plt.ipynb
 import math
 from typing import Union, Tuple, Any, Optional as O
 
@@ -15,7 +15,7 @@
 from .utils import get_config, config
 from .utils.utils import cached_property
 
-# %% ../nbs/02_repr_plt.ipynb 4
+# %% ../nbs/02_repr_plt.ipynb
 def normal_pdf( x   :np.ndarray,
                 mean:Union[np.ndarray, float] =0.,
                 std :Union[np.ndarray, float] =1.):
@@ -34,7 +34,7 @@ def normal_pdf( x   :np.ndarray,
                 (std * np.sqrt((np.pi * 2)))
             )
 
-# %% ../nbs/02_repr_plt.ipynb 6
+# %% ../nbs/02_repr_plt.ipynb
 def sample( x       :np.ndarray,
             max_s   :int,
             plt0    :bool):
@@ -60,7 +60,7 @@ def sample( x       :np.ndarray,
 
     return (x, x_min, x_max)
 
-# %% ../nbs/02_repr_plt.ipynb 7
+# %% ../nbs/02_repr_plt.ipynb
 def find_xlims( x_min   :Union[float, None],
                 x_max   :Union[float, None],
                 x_mean  :Union[float, None],
@@ -97,7 +97,7 @@ def find_xlims( x_min   :Union[float, None],
 
     return (xlim_min, xlim_max)
 
-# %% ../nbs/02_repr_plt.ipynb 8
+# %% ../nbs/02_repr_plt.ipynb
 def plot_histogram( x   :np.ndarray,
                     ax  :axes.Axes):
     if x.size:
@@ -115,7 +115,7 @@ def plot_histogram( x   :np.ndarray,
 
         ax.hist(x, bins=bins, color="deepskyblue", align="mid", density=True, zorder=4)
 
-# %% ../nbs/02_repr_plt.ipynb 9
+# %% ../nbs/02_repr_plt.ipynb
 def plot_pdf(   x_mean  :Union[float, None],
                 x_std   :Union[float, None],
                 ax      :axes.Axes):
@@ -129,7 +129,7 @@ def plot_pdf(   x_mean  :Union[float, None],
         ax.plot(xl, normal_pdf(xl, mean=x_mean, std=x_std), zorder=5)
 
 
-# %% ../nbs/02_repr_plt.ipynb 10
+# %% ../nbs/02_repr_plt.ipynb
 def plot_sigmas(x_min   :Union[float, None],
                 x_max   :Union[float, None],
                 x_mean  :Union[float, None],
@@ -152,7 +152,7 @@ def plot_sigmas(x_min   :Union[float, None],
                 ax.text(x_pos, ylims[1]*0.95, greek, ha="center", va="top", bbox=bbox, zorder=5, weight=weight)
 
 
-# %% ../nbs/02_repr_plt.ipynb 11
+# %% ../nbs/02_repr_plt.ipynb
 def plot_minmax(x_min   :Union[float, None],
                 x_max   :Union[float, None],
                 ax      :axes.Axes):
@@ -185,13 +185,13 @@ def plot_minmax(x_min   :Union[float, None],
         ax.axvline(x_max, 0, 1, c="red", zorder=2)
 
 
-# %% ../nbs/02_repr_plt.ipynb 12
+# %% ../nbs/02_repr_plt.ipynb
 def plot_str(t_str, ax):
     xlim = ax.get_xlim()
     ylim = ax.get_ylim()
     ax.text(xlim[0], ylim[1]*1.05, s=t_str)
 
-# %% ../nbs/02_repr_plt.ipynb 13
+# %% ../nbs/02_repr_plt.ipynb
 @config(show_mem_above=np.inf)
 def fig_plot(   x     :np.ndarray,  #
                 center  :str    ="zero",        # Center plot on  `zero`, `mean`, or `range`
@@ -248,7 +248,7 @@ def fig_plot(   x     :np.ndarray,  #
     return ax.figure
 
 
-# %% ../nbs/02_repr_plt.ipynb 14
+# %% ../nbs/02_repr_plt.ipynb
 # This is here for the monkey-patched tensor use case.
 # Gives the ability to call both .plt and .plt(ax=ax).
 
@@ -295,7 +295,7 @@ def _repr_svg_(self):
             svg_repr = print_figure(self.fig, fmt="svg", metadata=metadata)
         return svg_repr
 
-# %% ../nbs/02_repr_plt.ipynb 15
+# %% ../nbs/02_repr_plt.ipynb
 def plot(   x       :np.ndarray,        # Your data
             center  :str    ="zero",    # Center plot on  `zero`, `mean`, or `range`
             max_s   :int    =10000,     # Draw up to this many samples. =0 to draw all